# View Logs ## Feature Overview The **Logs** feature offers real-time insights into each input and output message within the dialog simulator, providing essential information that simplifies the debugging process and accelerates troubleshooting.

Log expanded. Click the pin next to the message to view details for that specific message.

### **Accessing Logs** The Logs can be accessed through the **dialog simulator** by clicking on the `Open log` (pin icon).

### **Key Functionalities**

Function	Description
Error Tracking and Identification	Displays a field detailing the error that occurred with that functionality, such as error type and precise timestamp (in milliseconds).
Detailed Information on Services	External Services: Logs show timestamps, error messages, error codes, service type, response, and metadata for all external service calls (e.g., Rest Connector, Prompt cell, Knowledge AI, Multilingual suppport, Webhook, Transactional answers). Gen AI services include prompt details, language model, tokens used, and temperature settings. Internal Services: Logs include information on internal components (e.g., NLP calls, masking, Knowledge AI), covering intent scores, error codes, and answers.
Exporting and Downloading	Logs can be downloaded in JSON format for documentation, further analysis, or archiving.
Entry Structure	Each entry is displayed as a single line for easy scanning, with comprehensive tracking of interactions, particularly for cells that call external services.
Filtering	Logs can be pinned to specific conversation points, allowing users to filter by message and trace errors to their origin within the dialog flow. You can filter logs based on date/time and type (info or error), ensuring an easier way to navigate.

The NLP option only appears when the agent is integrated with a NLP. If your agent is integrated with a LLM, Zero-Shot will appear instead. {% hint style="info" %} If you need a more in-depth insights into your analysis, try [**executing an Advanced Request task**](/testing/advanced-request.md) to assess your agent’s performance. {% endhint %} --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs-conversational-ai.syntphony.com/testing/view-logs.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.